Resource Sustainable Development Research Articles

Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference

Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protein production capacity and identify key factors. The extreme gradient boosting algorithm effectively predicted protein content, while the gradient boosting decision tree algorithm excelled in predicting protein production, protein productivity, and protein energy yields. Driving factors were identified, with suitable ranges: protein content (pH 6.0–7.5, hydraulic retention time (HRT) < 3.8 d), protein production (biomass > 1.7 g, organic loading rate (OLR) > 9.2 gL–1d–1, temperature 26.7–35.0 °C), protein productivity (HRT < 3.5 d, biomass > 1.6 g, OLR > 10.0 gL–1d–1), and protein energy yields (light energy 0.1–4.4 kWh, biomass 1.7–65.0 g, chemical oxygen demand (COD) 0.1–2.5 gL–1). Illuminance, dissolved oxygen, COD, and COD/total nitrogen ratio were causal factors influencing protein production. Two-dimensional partial dependence plot revealed the interaction between two driving factors. This study enhances information on PSB protein production and offers insights for wastewater treatment and sustainable resource development.

Groundwater potential and recharge zone mapping using GIS and remote sensing techniques: the Melka Kunture Watershed in Ethiopia

Groundwater is the most dynamic natural resource that is not uniformly distributed both in space and time. Identifying it for sustainable water resource development for domestic use, irrigation, and industrial purposes is the biggest challenge and key concern due to climate change, overexploitation, and a lack of proper management. Geographical information system (GIS) and remote sensing (RS) play a fundamental role in identifying suitable groundwater potential and recharge zones. In this study, groundwater potential and recharge zone map are delineated using GIS and RS techniques integrated with Analytic Hierarchy Process (AHP) for the Melka Kunture Watershed in Ethiopia. The thematic layers used were: Lithology, geomorphology, slope, lineament density, land use/cover, rainfall, drainage density and soil. GIS has been used to integrate and overlay thematic layers using a weighted overlay analysis tool, whereas the AHP method has been used to assign the weights, normalize, and rank thematic layers and their associated sub-themes based on their suitability, characteristics, or influence on groundwater potential and recharge zones. The output groundwater potential zone map is categorized into four suitable zones: high potential cover 1105.60 km2 (25.70%), moderate potential 2308.00 km2 (53.73%), low potential 880.0 km2 (20.49%), and very low potential 47.80 km2 (1.10%), whereas there are three suitable groundwater recharge potential zones: high potential cover 250.20 km2 (5.80%), moderate recharge 3647.90 km2 (84.00%), and low recharge 443.50 km2 (10.20%) of the study area. Hence, the study areas have been more suitable for groundwater potential and recharge zones as compared to the total area. The groundwater potential map was validated using the existing water source and well points, and it indicated a good prediction accuracy of 88%. Thus, the delineated groundwater potential and recharge zone maps are reliable, and the resultant potentiality mapping has played a vital role in the sustainable development and management of the water resources in the study area.

Intelligent Hazard Assessment of Mangrove Degradation

Mangrove ecosystems face multiple threats from human activities and natural disasters, posing a threat to their existence. The results of the automated system-cognitive analysis implemented in the intellectual system Eidos and allowing to assess the danger of degradation of mangrove forests are presented. Factors that have a negative and positive impact on the well-being of mangrove ecosystems are taken into account, and the strength and direction of the influence of each threat are determined. The results of the study can be used by coastal protection funds in many countries of the world due to the fact that the Eidos system is available free of charge on the Internet, and it is possible to change the user interface language to another most common language in the world. The application of the new research methodology will provide valuable information on the risk of degradation of mangrove forests in the current conditions of their growth in order to take timely measures for their conservation. By understanding the threats that the mangrove ecosystem faces, effective management practices can be applied that contribute to the conservation and sustainable development of this vital coastal resource

The adsorption and separation of tungsten and molybdenum by chitosan and chitosan-D301: Experiments and DFT theoretical calculation

The adsorption and separation of tungsten and molybdenum are important for efficient recycling of W-Mo resources, which requires green and efficient adsorbents. In this paper, Chitosan (CS)-D301 material was obtained by impregnation method and was applied to adsorb and separate W and Mo in solutions. The adsorption optimization results indicated that W was adsorbed by CS-D301, the separation factor of W/Mo increased to 26.45 compared with that of CS 21.34. The desorption efficiency was still above 94 % after five adsorption–desorption cycles. FT-IR, XPS and DFT theoretical calculations indicated that the surface group N+-R of CS-D301 showed more affinity for W, making it easier to selectively adsorb W over Mo than CS only. N was the surface-active adsorption site, and the adsorption process belonged to chemical adsorption with an adsorption energy of Eads = −957.64 kcal/mol. CS-D301 was expected to become green adsorbent for efficient separation of W and Mo to support resource recovery, protection and sustainable development.

The Effectiveness of the International Environmental Law: The Issues of State Sovereignty, National Interests, and Differing Levels of Commitments

This study aims to explore the main challenges facing international environmental law and affecting its effectiveness. Although many international texts and agreements have been adopted to address environmental degradation and promote sustainable resource development, most of these agreements remain ineffective in achieving the objectives of these agreements. The critical study reveals that these legal frameworks face many challenges that affect the effectiveness of these texts, for example, there are issues such as national sovereignty, the lack of unified implementation at the state level, insufficient funding, and weak institutional frameworks. This study aims to provide a comprehensive analytical view of the factors that affect the effectiveness of these texts and frameworks. The issues of national sovereignty, insufficient funding, weak institutional frameworks, different levels of commitment, lack of political will, and global cooperation will be mainly discussed here. By focusing on the most important challenges facing international environmental law, this research aims to contribute to developing international environmental law to make it more effective.

Quantifying the inequality of urban electric power consumption and its evolutionary drivers in countries along the belt and road: Insights from satellite perspective

Understanding regional inequalities in electricity resources is crucial for achieving sustainable development goals, yet relevant spatiotemporal information remains limited. This study develops a systematic framework using multi-source nighttime light remote sensing data and geographical methods to reveal the inequality in electric power consumption (EPC) and its drivers along the Belt and Road (B&R) countries from 2000 to 2019. The findings show that EPC in the B&R region increased by 8.8 trillion kWh over the past 20 years, with a shift in its geographic center, highlighting mid-latitude cities as major growth hotspots. Differences in between-group and within-group inequality patterns across various spatial scales lead to a scale effect on EPC inequality. The overall EPC inequality of B&R decreased by 20 % between 2000 and 2019, with inequality between countries being the main contributor, accounting for about 70 %. However, at the national level, within-province inequality is the predominant source in most countries. The analysis identifies three key drivers, with affluence having a more significant positive impact on EPC inequality than population or electricity dependence. These findings are valuable for the sustainable development of urban energy and regional electricity resource planning amidst long-term geographical changes.

Challenges of Indonesian Defense Resilience in the Face of Contemporary Technology Advancement: What’s Next?

This article discusses the concept of national resilience in the digital era, which extends beyond the paradigm of conventional warfare to address a wide range of challenges. To develop the concept of national resilience ideology, a conceptual research method with a philosophical approach is employed, supported by data triangulation using Miles and Huberman's method. The main findings highlight the importance of digital security and privacy, as well as the role of digital local wisdom in strengthening national identity. Additionally, increased legal awareness is considered crucial in shaping cultural norms, while the sustainable development of human resources, supported by quality education and healthcare services, remains a key focus

Land use dynamics and ecosystem service valuation in the Sanmenxia Reservoir wetland of the Yellow River

The Sanmenxia Reservoir wetland (SRW) serves as a critical ecological buffer in the middle reaches of the Yellow River. Ongoing population growth and changes in land use have placed significant pressure on the wetland’s ecosystems. However, existing research has yet to establish a spatiotemporal analysis method to assess the impact of land use change on the ecosystem service value (ESV). This gap hinders the precise regulation and sustainable development of land resources. To gain a comprehensive understanding of the land use dynamics and ecological functions of the SRW, this study introduced a refined ESV evaluation method. This method revised the equivalent factors from spatial, temporal, and hydrological perspectives, with an emphasis on the impact of sediment discharge. Furthermore, the Patch-level Land Use Simulation (PLUS) model was employed to project the land use structure in 2030, and the corresponding ESV was analyzed. The study revealed the following: (1) Cropland constituted the primary land type in the SRW. Over the last two decades, the build-up area exhibited the most significant single land use dynamics, with the transformation of bare land to cropland spanning the widest range and largest area. (2) From 2000 to 2020, the ESV increased by 0.64 billion CNY, with the water body contributing almost all the increase. (3) The projected ESV for 2030 is 2.94 billion CNY, indicating an increase in ecological functions in the near future. Policy makers should recognizethe impact of land use change on ESV and implement measures to rebalance land use structure. While ensuring the preservation of cropland and the protection of lives and property, it is advisable to consider expanding the water body area to facilitate comprehensive sustainable development within SRW.

Prediction and Analysis of Surface Residual Deformation Considering the Impact of Groundwater in Mines

With economic development and coal resource exploitation, the area of mined-out zones is expanding continuously. The traditional waste disposal methods no longer meet the current demands, making it urgent to evaluate and reuse the surface stability of these mined-out zones. Surface residual deformation is a process where voids and fissures within the mined-out zones are gradually filled and compacted, affecting the overlying rock structure. Additionally, groundwater significantly impacts the strength of the overlying rock, leading to increased subsidence. Therefore, predicting surface residual deformation while considering the effects of groundwater is crucial for forecasting surface deformation and assessing stability in mined-out zones. This study, taking into account the characteristics of subsidence zones and the impact of groundwater on the compaction of fractured rock masses, uses equivalent mining height and probability integral methods to develop a predictive model for surface residual deformation incorporating groundwater effects. Predictions for the study area show that groundwater exacerbates surface residual deformation, with various deformation values ranging from 33.8% to 51.9%. The surface stability categories are divided into stable and essentially stable regions based on the residual deformation’s impact on the working face. This model fully considers the influence of groundwater on residual deformation in mined-out zones, refining existing mining subsidence theories, addressing deformation issues caused by adverse groundwater factors, and providing a theoretical basis for predicting residual deformation and evaluating stability in mined-out zones, promoting the sustainable development of land and environmental resources in mining areas.

Hydrochemical Characteristics and Formation Mechanism of Geothermal Fluids in Zuogong County, Southeastern Tibet

Zuogong County is located in the southeast of Tibet, which is rich in hot spring geothermal resources, but its development and utilization degree are low, and the genetic mechanism of the geothermal system is not clear. Hydrogeochemical characteristics of geothermal water are of great significance in elucidating the genesis and evolution of geothermal systems, as well as the sustainable development and utilization of geothermal resources. The hydrogeochemical characteristics and genesis of the geothermal water in Zuogong County were investigated using hydrogeochemical analysis, a stable isotope (δD, δ18O) approach, and an inverse simulation model for water–rock reactions using the PHREEQC. The results indicated that the Zuogong geothermal system is a deep circulation heating type without a magmatic heat source. The chemical types present in the geothermal water from the Zuogong area are HCO3 and HCO3·SO4, and the main cations are Na+ and Ca2+. The groundwater is replenished by atmospheric precipitation and glacier meltwater. The salt content of geothermal water mainly comes from the interaction between water and surrounding rocks during the deep circulation process. The reservoir temperature of geothermal water in Zuogong is 120–176 °C before mixing with non-geothermal water and drops to 62–98 °C after mixing with 58 to 79% of non-geothermal water. According to the proposed conceptual model, geothermal water mainly produces water–rock interaction with aluminosilicate minerals in the deep formation, while in shallow areas it interacts mainly with sulfate minerals. These findings contribute to a better understanding of the geothermal system in Zuogong County, Tibet.

A method for estimating maximum safe installable power for groundwater extraction with application to Africa

New groundwater development is a likely way to meet growing global water demand but needs careful management. To help inform the sustainable development of groundwater resources, a novel method based on the maximum safe installable power for water pumping systems and the maximum safe remaining installable power (considering current abstraction) is developed. The proposed model couples energy, technology and hydrogeological parameters, and is then developed to compute the maximum power that can be safely installed per km2 without exceeding a maximum annual pumpable volume, calculated through available recharge and storage. The model is applied to estimate the maximum safe installable power across Africa with a 0.2-degree resolution, using available energy and hydrogeological data. Constrained by recharge (considering that 25 % of the annual recharge is available for utilization), the maximum safe installable power ranges between 0 and 9960 W/km2 across Africa with regions such as the Congo Basin (~340 W/km2), and western Africa between the Ivory Coast and Nigeria (~230 W/km2) identified as having high potential for sustainable pumping system development. Constrained by storage (considering that 0.1 % of storage can be withdrawn per year), it ranges between 0 and 13,425 W/km2 highlighting the ability to harness storage for pumping system development in the large aquifers of Northern Sahara (~8720 W/km2). When considering limitations posed by both groundwater recharge and aquifer storage (considering that 25 % of the annual recharge and 0.1 % of storage can be withdrawn per year), along with current groundwater withdrawal, 93 % of the maximum safe installable power remains still installable on average across Africa. Nevertheless, 2 % of the locations are estimated to be already experiencing overexploitation, particularly in Sudan, northern Africa, and northeastern South Africa. These findings provide a novel and adaptable way to examine water security, which can assist institutions in targeting investments to meet water demand sustainably.

Fireside Chat with Benjamin William Cashore: The Role of National Policies in Driving Sustainable Development of Vital Resources

Fireside Chat with Benjamin William Cashore: The Role of National Policies in Driving Sustainable Development of Vital Resources

Sustainable development and utilization of marine genetic resources in areas beyond national jurisdiction: A Chinese perspective.

Breakthroughs in marine science and technology have profoundly expanded our knowledge of the ocean, driving unprecedented levels of marine resource utilization. Consequently, the immense value of marine genetic resources (MGRs) in areas beyond national jurisdiction (ABNJ) has catapulted them to the forefront of international competition. In response to the existing gap in international legal frameworks governing the conservation and sustainable use of biodiversity in ABNJ, the Agreement under the United Nations Convention on the Law of the Sea on the Conservation and Sustainable Use of Marine Biological Diversity of Areas Beyond National Jurisdiction (BBNJ Agreement) was adopted on 19 June 2023. This study aimed to explore China's participation in this new frontier of global ocean governance, focusing on the opportunities and challenges it faces. By employing document analysis and policy analysis, the study delved into international legal frameworks such as the United Nations Convention on the Law of the Sea (UNCLOS) and the BBNJ Agreement, as well as China's domestic policies related to marine resource development. It systematically examined the relevant legal frameworks and their historical contexts. Additionally, comparative analysis was used to contrast the policy-making and development practices of developed and developing countries, allowing for a comprehensive assessment of China's role and challenges in the sustainable use of MGRs in ABNJ. It is concluded that while China has made remarkable progress in MGR research, it still lags behind traditional maritime powers in patent accumulation and the commercialization of MGRs. China also lacks comprehensive domestic legislation to address issues such as benefit-sharing and effective regulation of MGRs in ABNJ. Therefore, China must enhance its scientific research and innovation capabilities, actively participate in the follow-up work of the BBNJ Agreement, and promote global marine biodiversity conservation guided by the concept of a Maritime Community with a Shared Future.

Recycling impacts of renewable energy generation-related rare earth resources: A SWOT-based strategical analysis

As the global energy mix transforms and renewable energy technologies rapidly develop, there has been a significant increase in the demand for rare earth elements, which play a crucial role in renewable energy systems. By recycling rare earth resources from obsolete equipment, the reliance on newly mined rare earth resources can be reduced, thereby reducing the related environmental and energy footprints and increasing the stability of the supply chain. This study aims to systematically and strategically analyze and discuss the recycling impacts of renewable energy generation (REG)-related rare earth resources in terms of environmental, economic, social, and governance aspects. A SWOT strategical analysis framework integrating a management cycle and intelligent text data mining is built to address the above tasks from an ESG (Environment, Society, and Governance) perspective. The SWOT analysis of the rare earth recycling impacts focuses on strengths (e.g., reduced dependence on rare resources, reduced environmental and emission pressure), weaknesses (e.g., high cost, technology and management complexity), opportunities (e.g., policy support, technological innovations, diversification of the global supply chain), and threats (e.g., market volatility, the emergence of alternative materials). This analysis framework reveals textual topic changes and suggests cyclic and strategical improvement pathways to analyze the multi-dimensional recycling impacts. The text data analysis results indicate that the trend of rare earth recycling is gradually transformed from technologies, supply and demand, and secondary resources into resource and environment sustainable development. Beyond overcoming identified challenges, future pathways should focus more on the integration of advanced emerging technologies, life cycle management, and dynamic adjustment of recycling strategies. This study could provide policymakers and industry practitioners with recommendations and outlook on current development status and improvement strategies to promote REG-related rare earth recycling.

Well-Being and Sustainable Utilization of Forest Environment with Diverse Vegetation Distributions

Forest landscape space is the basic unit of forest landscape resources. Healthy forest landscape resources can not only improve the sustainable cycle of forest ecological service function, but also have a positive impact on human health and well-being. Evidence supports the view that the forest environment is beneficial to people’s health, and further discussion of the dose response between environmental attributes and physical and mental recovery has been widely carried out by scholars. As an important component of environmental attributes, it is necessary to clarify the relationship between vegetation distribution and users’ health in order to better plan, design, and utilize forest environmental resources. This study mainly used the virtual immersive forest environment video in VR, and used the difference test in SPSS 23.0 to clarify whether the distribution of vegetation in the forest environment will affect the physiological and psychological recovery effect of users. The main results are as follows: (1) Experiencing the forest environment can promote users’ physiological and psychological health, and its recovery effect is significantly better than the indoor environment (p &lt; 0.05). (2) The distribution of vegetation in the forest environment will affect users’ physiological and psychological recovery effect. Among them, in the cluster and randomly distributed forest environments, the relaxation and concentration of users can be improved mainly by alleviating their negative emotions. In the evenly distributed forest environment, users mainly achieve the purpose of relaxation by improving their vitality and positive emotions. These results show that the distribution of vegetation is one of the factors for the restoration of forest environment. In the future design and management of the forest environment, the health and well-being of users can be effectively enhanced by getting involved with the vegetation distribution in the site, aiming to provide a scientific basis for the promotion of the rehabilitation function of forest landscape space and its sustainable utilization, thus promoting the sustainable development of forest resources and improving people’s quality of life.

Identifying the spatio-temporal distribution characteristics of offshore wind turbines in China from Sentinel-1 imagery using deep learning

ABSTRACT Offshore wind power is a crucial clean energy source for coastal countries and advances blue economies. Accurate spatial mapping of offshore wind turbines supports energy assessment and the sustainable development of marine resources. Offshore wind power has developed rapidly in China, but the spatiotemporal distribution characteristics of offshore wind turbines and farms remain poorly understood. Extracting nearshore small targets from Sentinel-1 synthetic aperture radar images remain challenging due to noise from the rough sea surface background and the diverse substrate types in offshore wind turbine (OWT) distributions. Here, to address these issues, we first created a dataset of China’s offshore wind turbines (COWTs) that contained typical substrate types (e.g. seawater and tidal flats). Then, a deep learning model integrating an attention mechanism and receptive fields was used to accurately detect COWTs. The well-trained model was used to detect the changes in COWTs from 2015 to 2022. Our model detected an increase in the number of offshore wind farms in China from 7 to 114 (clusters counted as an offshore wind farm), while COWTs increased from 305 to 6451 from 2015 to 2022. The Taiwan Strait exhibited the highest wind speeds, yet the Jiangsu and Guangdong regions had the most installed turbines. Over 90% of COWTs were located in areas with offshore wind energy resources less than 500 W/m3, indicating a mismatch between COWT installation and wind resource distribution. This study demonstrated temporal and geographical generalizability, which is promising for global wind power detection. Our analysis of spatiotemporal variation in COWTs facilitates informed decision-making for future field establishment and sustainable marine planning.

Achieving Sustainable Resource Development: A State-of-the-Art Understanding of Blue-Green Water

Achieving Sustainable Resource Development: A State-of-the-Art Understanding of Blue-Green Water

Robust estimation of hydrogeological parameters from wireline logs usingsemi-supervised deep neural networks assisted with global optimization-based regression methods

Understanding the distribution of hydrogeological properties of the aquifers is crucial for sustainable groundwater resource development. This research explores the application of deep autoencoder neural networks (AE-NN), assisted with global optimization methods for estimating hydrogeological parameters in the Quaternary aquifer system in the Debrecen area, Hungary. Traditional methods for estimating aquifer parameters typically depend on field experiments and laboratory analyses, which are both costly and time-consuming, and often fail to account for the heterogeneity of groundwater formations. In this study, deep AE-NN models are trained to extract latent space (LS) representations that capture key features from the available well logs, including spontaneous potential (SP), natural gamma ray (NGR), shallow resistivity (RS), and deep resistivity (RD). The LS log is then correlated with shale volume and hydraulic conductivity, as determined by the Larionov and Csókás methods, respectively. Regression analysis revealed a Gaussian relationship between the LS log and shale volume and a negative nonlinear relationship with hydraulic conductivity. Global optimization methods, including simulated annealing (SA) and particle swarm optimization (PSO), were used to refine the regression parameters, enhancing the predictive capabilities of the models. The results demonstrated that AE-NN assisted with global optimization methods can be effectively used to estimate shale volume and hydraulic conductivity, proposing a novel and independent approach for estimating hydrogeological parameters critical to groundwater flow and contaminant transport modeling.

Nitrogen reduction enhances crop productivity, decreases soil nitrogen loss and optimize its balance in wheat-maize cropping area of the Loess Plateau, China

In winter wheat-summer maize double cropping, fertilization changes the nitrogen (N) balance in the soil N pool, grain N uptake, N loss, and nitrogen use efficiency (NUE), ultimately impacting crop productivity and environmental health. For agricultural systems to maintain yields at lower environmental costs, N budgets must be balanced. Still, there is a deficiency in the reporting of N budgets of farming systems that incorporate all N flows. We evaluated the effects of various N fertilizer application rates on soil N balance and crop productivity in the 2017–2021 winter wheat-summer maize growing seasons. These rates included non-N fertilization (N0), 75 kg·N·ha−1 (N75), 150 kg·N·ha−1 (N150), 225 kg·N·ha−1 (N225), and conventional N fertilizer application rate, 300 kg·N·ha−1 (N300). Our analysis was based on a long-term field fertilization experiment and in-situ observation (established in 2010). The results show that fertilization significantly increased crop yields (wheat: 29.2 %–97.6 %; maize:25.4 %–98.1 %; annal: 27.0 %–96.7 %), among which N225 showed the highest increase value, compared with N0. Moreover, the N225 maximized grain N uptake by 201.0 %, reducing N losses and increasing N sequestration compared to the conventional N application rate of N300. N balance changes from negative to positive as the N application rate increases (wheat: −63.78–85.24 kg·ha−1; maize: −55.77–82.25 kg·ha−1; annal: −119.58–167.46 kg·ha−1·yr−1). Combining years of N inputs and outputs, the N225 is more balanced. Therefore, our study shows that an appropriate reduction of N fertilizer (N225) can help maintain agricultural productivity and promote N sequestration in farmland by reducing environmental N loss. Maintaining the virtuous cycle of N in the farmland ecosystem is beneficial and essential for the efficient utilization, high yield, and sustainable development of farmland resources.

Sustainable development of fishery resources: Precipitation of protein from surimi rinsing wastewater by low-temperature plasma

This study aimed to determine the impact of low-temperature plasma (LTP) on the protein stability and composition in surimi rinsing wastewater (SRW). When SRW (300 mL) was treated with LTP at a power of 420 W and a flow rate of 1.1 L/min for 106 s, the protein precipitation was 76.04 %, the pH was close to the estimated value of the isoelectric point (pI). In comparison with the pI precipitation treatment, non-precipitated proteins in the SRW after LTP precipitation treatment showed significant changes in amino acids susceptible to oxidation but had minor changes in the hydrophobic amino acid content. LTP showed a markedly differentiated response to the different protein types in the SRW, increasing the relative amounts of several enzyme proteins in the non-precipitated protein. The combined effect of the active ingredients provided by LTP on protein conformation and hydrophobic interactions may be responsible for this ‘screening’ phenomenon.